COURSE UNIT TITLE

: NEURAL ENGINEERING

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
BMT 0609 NEURAL ENGINEERING ELECTIVE 3 0 0 6

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

ASSISTANT PROFESSOR AYLIN ŞENDEMIR ÜRKMEZ

Offered to

Industrial Ph.D. Program In Advanced Biomedical Technologies
Industrial Ph.D. Program In Advanced Biomedical Technologies

Course Objective

Applying engineering to neuroscience including such diverse areas as neural tissue engineering, models of neural function, and neural interface technology.

Learning Outcomes of the Course Unit

1   To learn fundamental structures and mechanisms of neural system,
2   Understand the current challenges in neural engineering and the directions in which thearea is headed,
3   Getting knowledge about neural diseases and current treatment techniques.
4   To learn alternative techniques for neural disease diagnosis and treatment.
5   To learn how to make a literature review in order to find a technical paper on any subject of the course, to read, summarize and present the study orally.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to nervous system, nervous system cells, classification of neurons, neurotransmitters;
2 Macro-anatomy of neural system, central nervous system, peripheral nervous system, sympathetic and parasympathetic nervous system;
3 Neural system diseases and current treatment techniques;
4 Different types of animals, cells and tissue models that are currently being used neural system research;
5 Neural channels;
6 Neural engineering applications for peripheral nervous system;
7 Neural engineering applications for central nervous system;
8 Techniques for mapping neural pathways and it s connections;
9 Behavioral studies in neuroscience;
10 Electrophysiological techniques that are being used in Neural Engineering studies;
11 Biochemical and molecular techniques that are being used in Neural Engineering applications;
12 Imaging techniques in neuroscience
13 Backwards engineering techniques in neural engineering;
14 Introduction to neural networks; Ethical issues in neuroscience;

Recomended or Required Reading

1. David Zhoua and Elias Greenbaum, Implantable Neural Prothesis 2: Tecqniques and Engineering Approaches ,Springer (2009).
2. Nick Van Bruggen and Timothy P.L. Roberts, Biomedical Imaging in Experimental Neuroscience (Fronties in Neuroscience) , CRC Press (2002).
3. Daniel J. DiLorenzo, Joseph D. Bronzino, Neuroengineering , CRC Press (2007).
4. MetinAkay, Handbook of Neural Engineering (IEEE Press Series on Biomedical Engineering) , Wiley-IEEE Press, (2007).
5. Scientific articles provided during the semester

Planned Learning Activities and Teaching Methods

Project and exams

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.20 + ASG * 0.20 + FIN * 0.60
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.20 + ASG * 0.20 + RST * 0.60


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Design Project 1 25 25
Preparations before/after weekly lectures 14 2 28
Preparation for midterm exam 1 10 10
Preparation for final exam 1 20 20
Reading 14 2 28
Preparing presentations 1 1 1
Final 1 1 1
Midterm 1 1 1
TOTAL WORKLOAD (hours) 156

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.1545
LO.2415
LO.33
LO.422
LO.54